Dynamic Risk Prediction for Cardiovascular Disease: An Illustration Using the ARIC Study

Jessica K. Barrett*, Michael J. Sweeting, Angela M. Wood

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Citation (Scopus)

Abstract

We review methods for using repeated measurements of a time-varying risk predictor in dynamic risk prediction. We compare how the landmarking and joint modeling approaches can incorporate information from repeated measurements of systolic blood pressure in cardiovascular risk prediction and illustrate the methods using data from the Atherosclerosis Risk in Communities Study. We assess predictive accuracy using dynamic measures of discrimination and calibration.

Original languageEnglish
Title of host publicationHandbook of Statistics
PublisherElsevier B.V.
Pages47-65
Number of pages19
DOIs
Publication statusPublished - 2017
Externally publishedYes

Publication series

NameHandbook of Statistics
Volume36
ISSN (Print)0169-7161

Bibliographical note

Publisher Copyright:
© 2017 Elsevier B.V.

Keywords

  • Cardiovascular disease
  • Dynamic prediction
  • Joint models
  • Landmarking
  • Predictive accuracy
  • Repeated measurements
  • Survival analysis

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